Applied AI Engineer, Enterprise Tech
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA · Sales
About this role
Anthropic is hiring a mid-level Machine Learning Engineer based in San Francisco, CA | New York City, NY | Seattle, WA. The posting calls out experience with Python, TypeScript, LLMs, Prompt Engineering. Compensation is listed at $200,000–$320,000 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY | Seattle, WA
- Department
- Sales
More roles at Anthropic
Job description
from Anthropic careersAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to Digital Native Businesses - technology companies adopting the Claude API into their core products. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting-edge implementation patterns for LLMs.
Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.
Responsibilities:
- Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success